Published 9/2024
Created by Phuzo Soko
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 25 Lectures ( 5h 7m ) | Size: 2.68 GB

Developing ETLs on Azure, Amazon Web Services (AWS) and Google Cloud Platform (GCP)

What you'll learn:
General understanding of Data Integration in Azure, Amazon Web Services, Google Cloud Platform
To gain the ability to muster necessary services in Azure, Amazon Web Services, Google Cloud Platform to create a funtional ETL
To be able to justify the choice of Data Integration services selected for a particular use case
To be able to create a functional ETL in Azure, Amazon Web Services, Google Cloud Platform using the available services
Requirements:
Previous ETL experience is needed. However a keen beginner could follow and be able to attain the learning outcomes stipulated above
Previous experience in the Data Ecosystem areas such Data Engineering, Data warehousing or Business Intelligence to whom ETL is not a new concept. However, those who are keen to get their hands dirty without the said prerequisites can also benefit from the course if they follow it closely and enrich its contents with other resources
Description:
The course "ETLs on Cloud Platforms Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)" is designed to provide a comprehensive understanding of Extract, Transform, Load (ETL) processes across the three most widely used cloud platforms. The primary objective is to equip learners with the knowledge and skills to effectively design, develop, and manage ETL pipelines on Azure, AWS, and GCP, each of which offers unique tools and services for data integration.The course starts by building a strong foundation in ETL fundamentals, helping learners understand the principles of extracting data from various sources, transforming it into usable formats, and loading it into target systems. It then delves into the specific ETL tools and services provided by each cloud platform-Azure Data Factory, AWS Glue, and Google Cloud Data Fusion-ensuring that students can navigate and utilize these platforms effectively.One of the key focuses of the course is on building scalable and efficient data pipelines that can handle large-scale data processing tasks. It also emphasizes optimization techniques for enhancing performance while minimizing costs, an essential aspect of cloud-based ETL operations. Moreover, the course covers best practices for ensuring data security and compliance with industry regulations, which is critical in today's data-driven world.Hands-on experience is a significant component of the course, with real-world scenarios that enable learners to apply what they've learned in practical settings. Additionally, the course explores cross-platform interoperability, teaching students how to design ETL processes that can operate seamlessly across Azure, AWS, and GCP.By the end of the course, participants will be equipped with the expertise to implement robust and efficient ETL solutions on any of these cloud platforms, preparing them for advanced roles in cloud data engineering and enhancing their career prospects in the rapidly evolving field of cloud computing.
Who this course is for:
Intermediate to advanced Data Engineering, Data warehousing or Business Intelligence Developers
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